Python simulation framework for Collision Avoidance for Unmanned Surface Vehicle using Deep Reinforcement Learning.
An explanation of the software structure can be found in Eivind Meyers repository gym-auv
Note: Requires Python 3.7
Note: Pybullet needs Microsoft Visual C++ 14.0. Install it with "Build Tools for Visual Studio".
Note: Stable-Baselines only supports Tensorflow 1.14, Tensorflow 2 support is planned.
! Install Microsoft MPI (https://docs.microsoft.com/en-us/message-passing-interface/microsoft-mpi) (msmpisetup.exe , not SDK)
Note: Run the following first.
conda install -c conda-forge shapely
conda install swig
conda install ffmpeg
Then run
pip install -e ./gym-auv/
You can now execute the script by running
python run.py <mode> <env>
The run script can be executed with the -h flag for a comprehensive overview of the available usage modes.
Examples:
python run.py play TestScenario1-v0
python run.py train MovingObstaclesNoRules-v0
python run.py enjoy MovingObstaclesNoRules-v0 --algo algorithm --agent path\to\agent.pkl
- terrain.npy is missing from "resources/" because github does not support uploading large files. (reach out for a copy of this file)
- Lots of deprecation warnings because of TensorFlow 1